{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time Window Features\n",
    "\n",
    "Run this notebook in Vertex Workbench. In this notebook, we will look at the behavior of delays over time.\n",
    "\n",
    "The method used in this notebook violates causality constraints. We'll do time windows properly in Dataflow."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Delays at airport\n",
    "\n",
    "What's the behavior of arrival delays at a specific airport?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 679.02query/s] \n",
      "Downloading: 100%|██████████| 765/765 [00:01<00:00, 713.91rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery dfw\n",
    "\n",
    "SELECT\n",
    "  dep_time,\n",
    "  arr_delay\n",
    "FROM dsongcp.flights_tzcorr\n",
    "WHERE\n",
    "  ORIGIN = 'DFW' AND FL_DATE = '2015-03-02'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>arr_delay</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dep_time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-03-02 06:53:00+00:00</th>\n",
       "      <td>147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02 11:09:00+00:00</th>\n",
       "      <td>-16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02 11:18:00+00:00</th>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02 11:37:00+00:00</th>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02 11:42:00+00:00</th>\n",
       "      <td>-12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           arr_delay\n",
       "dep_time                            \n",
       "2015-03-02 06:53:00+00:00      147.0\n",
       "2015-03-02 11:09:00+00:00      -16.0\n",
       "2015-03-02 11:18:00+00:00       10.0\n",
       "2015-03-02 11:37:00+00:00       -5.0\n",
       "2015-03-02 11:42:00+00:00      -12.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfw_plot = dfw.sort_values(by='dep_time').set_index('dep_time');\n",
    "dfw_plot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "sns.set(rc={'figure.figsize':(20, 5)})\n",
    "ax = dfw_plot['arr_delay'].plot(linewidth=2);\n",
    "ax.set_ylabel('delay (minutes)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rolling average\n",
    "\n",
    "What does the rolling average behave like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 2/2 [00:00<00:00, 950.87query/s]                         \n",
      "Downloading: 100%|██████████| 765/765 [00:01<00:00, 752.21rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery dfw\n",
    "\n",
    "SELECT\n",
    "  dep_time,\n",
    "  AVG(dep_delay) OVER time_window AS dep_delay,\n",
    "  AVG(arr_delay) OVER time_window AS arr_delay\n",
    "FROM dsongcp.flights_tzcorr\n",
    "WHERE\n",
    "  ORIGIN = 'DFW' AND FL_DATE = '2015-03-02'\n",
    "WINDOW time_window AS (ORDER BY UNIX_SECONDS(dep_time) \n",
    "                       RANGE BETWEEN 3600 PRECEDING AND 1 PRECEDING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfw_plot = dfw.sort_values(by='dep_time').set_index('dep_time');\n",
    "ax = dfw_plot['arr_delay'].plot(linewidth=2);\n",
    "dfw_plot['dep_delay'].plot(linewidth=2, ax=ax);\n",
    "ax.set_ylabel('rolling average delay (minutes)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Taxiout by airport\n",
    "\n",
    "Does taxi out time vary by airport? Is the same value of taxiout associated with late arrivals in one airport, but normal in another?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 2/2 [00:00<00:00, 981.35query/s]                         \n",
      "Downloading: 100%|██████████| 30/30 [00:01<00:00, 26.53rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery txout\n",
    "\n",
    "SELECT\n",
    "  ORIGIN,\n",
    "  IF (arr_delay < 15, True, False) AS is_on_time,\n",
    "  AVG(taxi_out) AS taxi_out\n",
    "FROM dsongcp.flights_tzcorr\n",
    "WHERE SUBSTR(ORIGIN, 1, 1) = 'D'\n",
    "GROUP BY ORIGIN, is_on_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>is_on_time</th>\n",
       "      <th>taxi_out</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DLG</td>\n",
       "      <td>True</td>\n",
       "      <td>7.171429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DVL</td>\n",
       "      <td>True</td>\n",
       "      <td>16.209713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DVL</td>\n",
       "      <td>False</td>\n",
       "      <td>21.906667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DLG</td>\n",
       "      <td>False</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DAY</td>\n",
       "      <td>True</td>\n",
       "      <td>14.246298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ORIGIN  is_on_time   taxi_out\n",
       "0    DLG        True   7.171429\n",
       "1    DVL        True  16.209713\n",
       "2    DVL       False  21.906667\n",
       "3    DLG       False   9.000000\n",
       "4    DAY        True  14.246298"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "txout.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "txout = txout.sort_values(by='ORIGIN')\n",
    "sns.barplot(data=txout, x='ORIGIN', y='taxi_out', hue='is_on_time');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add new features\n",
    "\n",
    "Let's add these two features and train an xgboost model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 7/7 [00:00<00:00, 3075.33query/s]                        \n",
      "Downloading: 100%|██████████| 5/5 [00:01<00:00,  4.85rows/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ontime</th>\n",
       "      <th>dep_delay</th>\n",
       "      <th>avg_dep_delay</th>\n",
       "      <th>taxi_out</th>\n",
       "      <th>avg_taxi_out</th>\n",
       "      <th>distance</th>\n",
       "      <th>origin</th>\n",
       "      <th>dest</th>\n",
       "      <th>is_eval_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ontime</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.313258</td>\n",
       "      <td>425.0</td>\n",
       "      <td>ABE</td>\n",
       "      <td>DTW</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ontime</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.313258</td>\n",
       "      <td>692.0</td>\n",
       "      <td>ABE</td>\n",
       "      <td>ATL</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ontime</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.313258</td>\n",
       "      <td>692.0</td>\n",
       "      <td>ABE</td>\n",
       "      <td>ATL</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ontime</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.313258</td>\n",
       "      <td>425.0</td>\n",
       "      <td>ABE</td>\n",
       "      <td>DTW</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ontime</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.313258</td>\n",
       "      <td>654.0</td>\n",
       "      <td>ABE</td>\n",
       "      <td>ORD</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ontime  dep_delay  avg_dep_delay  taxi_out  avg_taxi_out  distance origin  \\\n",
       "0  ontime       -8.0            NaN      12.0     13.313258     425.0    ABE   \n",
       "1  ontime       -7.0           -8.0      13.0     13.313258     692.0    ABE   \n",
       "2  ontime        0.0            NaN       9.0     13.313258     692.0    ABE   \n",
       "3  ontime        0.0            NaN       9.0     13.313258     425.0    ABE   \n",
       "4  ontime        7.0            0.0       8.0     13.313258     654.0    ABE   \n",
       "\n",
       "  dest  is_eval_day  \n",
       "0  DTW        False  \n",
       "1  ATL        False  \n",
       "2  ATL        False  \n",
       "3  DTW         True  \n",
       "4  ORD         True  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "WITH taxiout_by_airport AS (\n",
    "   SELECT \n",
    "    ORIGIN, AVG(taxi_out) AS avg_taxi_out\n",
    "   FROM\n",
    "    dsongcp.flights_tzcorr\n",
    "   GROUP BY ORIGIN\n",
    ")\n",
    "\n",
    "SELECT\n",
    "  IF(arr_delay < 15, 'ontime', 'late') AS ontime,\n",
    "  dep_delay,\n",
    "  AVG(dep_delay) OVER (origin_time_window) AS avg_dep_delay,\n",
    "  taxi_out,\n",
    "  avg_taxi_out,\n",
    "  distance,\n",
    "  origin,\n",
    "  dest,\n",
    "  IF(is_train_day = 'True', False, True) AS is_eval_day\n",
    "FROM dsongcp.flights_tzcorr f\n",
    "JOIN dsongcp.trainday t\n",
    "ON f.FL_DATE = t.FL_DATE\n",
    "JOIN taxiout_by_airport USING(ORIGIN)\n",
    "WHERE\n",
    "  f.CANCELLED = False AND \n",
    "  f.DIVERTED = False\n",
    "WINDOW origin_time_window AS (PARTITION BY ORIGIN\n",
    "                              ORDER BY UNIX_SECONDS(dep_time) \n",
    "                              RANGE BETWEEN 3600 PRECEDING AND 1 PRECEDING)\n",
    "\n",
    "LIMIT 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 3/3 [00:00<00:00, 1655.86query/s]                        \n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "  </thead>\n",
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       "Empty DataFrame\n",
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   ],
   "source": [
    "%%bigquery\n",
    "CREATE OR REPLACE MODEL dsongcp.arr_delay_airports_timefeatures\n",
    "OPTIONS(input_label_cols=['ontime'], \n",
    "        model_type='boosted_tree_classifier',\n",
    "        data_split_method='custom',\n",
    "        data_split_col='is_eval_day')\n",
    "AS\n",
    "\n",
    "WITH taxiout_by_airport AS (\n",
    "   SELECT \n",
    "    ORIGIN, AVG(taxi_out) AS avg_taxi_out\n",
    "   FROM\n",
    "    dsongcp.flights_tzcorr\n",
    "   GROUP BY ORIGIN\n",
    ")\n",
    "\n",
    "SELECT\n",
    "  IF(arr_delay < 15, 'ontime', 'late') AS ontime,\n",
    "  dep_delay,\n",
    "  AVG(dep_delay) OVER origin_time_window AS avg_dep_delay,\n",
    "  taxi_out,\n",
    "  avg_taxi_out,\n",
    "  distance,\n",
    "  origin,\n",
    "  dest,\n",
    "  IF(is_train_day = 'True', False, True) AS is_eval_day\n",
    "FROM dsongcp.flights_tzcorr f\n",
    "JOIN dsongcp.trainday t\n",
    "ON f.FL_DATE = t.FL_DATE\n",
    "JOIN taxiout_by_airport USING(ORIGIN)\n",
    "WHERE\n",
    "  f.CANCELLED = False AND \n",
    "  f.DIVERTED = False\n",
    "WINDOW origin_time_window AS (PARTITION BY ORIGIN\n",
    "                              ORDER BY UNIX_SECONDS(dep_time) \n",
    "                              RANGE BETWEEN 3600 PRECEDING AND 1 PRECEDING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 7/7 [00:00<00:00, 3130.08query/s]                        \n",
      "Downloading: 100%|██████████| 1/1 [00:00<00:00,  1.01rows/s]\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>correct_cancel</th>\n",
       "      <th>total_noncancel</th>\n",
       "      <th>correct_noncancel</th>\n",
       "      <th>total_cancel</th>\n",
       "      <th>rmse</th>\n",
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       "      <th>0</th>\n",
       "      <td>0.842506</td>\n",
       "      <td>1305656</td>\n",
       "      <td>0.965773</td>\n",
       "      <td>283750</td>\n",
       "      <td>0.20406</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   correct_cancel  total_noncancel  correct_noncancel  total_cancel     rmse\n",
       "0        0.842506          1305656           0.965773        283750  0.20406"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "\n",
    "WITH predictions AS (\n",
    "SELECT \n",
    "  *\n",
    "FROM ML.PREDICT(MODEL dsongcp.arr_delay_airports_timefeatures,\n",
    "                 (\n",
    "WITH taxiout_by_airport AS (\n",
    "   SELECT \n",
    "    ORIGIN, AVG(taxi_out) AS avg_taxi_out\n",
    "   FROM\n",
    "    dsongcp.flights_tzcorr\n",
    "   GROUP BY ORIGIN\n",
    ")\n",
    "SELECT\n",
    "  IF(arr_delay < 15, 'ontime', 'late') AS ontime,\n",
    "  dep_delay,\n",
    "  AVG(dep_delay) OVER origin_time_window AS avg_dep_delay,\n",
    "  taxi_out,\n",
    "  avg_taxi_out,\n",
    "  distance,\n",
    "  origin,\n",
    "  dest,\n",
    "  IF(is_train_day = 'True', False, True) AS is_eval_day\n",
    "FROM dsongcp.flights_tzcorr f\n",
    "JOIN dsongcp.trainday t\n",
    "ON f.FL_DATE = t.FL_DATE\n",
    "JOIN taxiout_by_airport USING(ORIGIN)\n",
    "WHERE\n",
    "  f.CANCELLED = False AND \n",
    "  f.DIVERTED = False AND\n",
    "  t.is_train_day = 'False'\n",
    "WINDOW origin_time_window AS (PARTITION BY ORIGIN\n",
    "                              ORDER BY UNIX_SECONDS(dep_time) \n",
    "                              RANGE BETWEEN 3600 PRECEDING AND 1 PRECEDING)\n",
    "                 ),\n",
    "                 STRUCT(0.7 AS threshold))),\n",
    "\n",
    "stats AS (\n",
    "SELECT \n",
    "  COUNTIF(ontime != 'ontime' AND ontime = predicted_ontime) AS correct_cancel\n",
    "  , COUNTIF(predicted_ontime = 'ontime') AS total_noncancel\n",
    "  , COUNTIF(ontime = 'ontime' AND ontime = predicted_ontime) AS correct_noncancel\n",
    "  , COUNTIF(ontime != 'ontime') AS total_cancel\n",
    "  , SQRT(SUM((IF(ontime = 'ontime', 1, 0) - p.prob) * (IF(ontime = 'ontime', 1, 0) - p.prob))/COUNT(*)) AS rmse\n",
    "FROM predictions, UNNEST(predicted_ontime_probs) p\n",
    "WHERE p.label = 'ontime'\n",
    ")\n",
    "\n",
    "SELECT\n",
    "   correct_cancel / total_cancel AS correct_cancel\n",
    "   , total_noncancel\n",
    "   , correct_noncancel / total_noncancel AS correct_noncancel\n",
    "   , total_cancel\n",
    "   , rmse\n",
    "FROM stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright 2021 Google Inc. Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
   ]
  }
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